Genes for the high life： New genetic variants point to positive selection for high altitude hypoxia in Tibetans

People living on the high plateaus of the world have long fascinated biological anthropologists and geneticists because they live in ＂thin air＂ and epitomize an extreme of human biological adaptation.

Rice molecular markers and genetic mapping:Current status and prospects

Dramatic changes in climatic conditions that supplement the biotic and abiotic stresses pose severe threat to the sustainable rice production and have made it a difficult task for rice molecular breeders to enhance production and productivity under these stress factors. The main focus of rice molecular breeders is to understand the fundamentals of molecular pathways involved in complex agronomic traits to increase the yield. The availability of complete rice genome sequence and recent improvements in rice genomics research has made it possible to detect and map accurately a large number of genes by using linkage to DNA markers. Linkage mapping is an effective approach to identify the genetic markers which are co-segregating with target traits within the family. The ideas of genetic diversity, quantitative trait locus（QTL） mapping, and marker-assisted selection（MAS） are evolving into more efficient concepts of linkage disequilibrium（LD） also called association mapping and genomic selection（GS）, respectively. The use of cost-effective DNA markers derived from the fine mapped position of the genes for important agronomic traits will provide opportunities for breeders to develop high-yielding, stress-resistant, and better quality rice cultivars. Here we focus on the progress of molecular marker technologies, their application in genetic mapping and evolution of association mapping techniques in rice.

Integrity of Four Theories on Natural Selection Unit

[Objective] The aim was to study the internal relationship of the four theories on natural selection unit. [Method] The value field of fitness of heterozygote was investigated by constructing mathematical models, to clarify the internal relations of the four theories on natural selection unit. [Result] According to mathematical modes constructed in the study, only the mutated genes meet the requirements of natural selection on heterozygous and homozygous aspects, as well as show high fitness in heterozygous condition, could the mutated genes be kept, giving consideration to both individual and population adaptation. Thus, this methodology theoretically inte- grates the theories of individual selection, collective selection, and genetic selection as well as Kimura＇s neutral theory of health information. [Conclusion] The result of this study suggested that the four theories on natural selection unit can co-exist, and share common premises.

Response to Selection for Fast Growth in the Second Generation of Pacific Oyster (Crassostrea gigas)

Mass selection for fast growth was conducted in three Pacific oyster (Crassostrea gigas) stocks from China, Japan and Korea using previously established lines (CS1, JS1, and KS1). To determine whether continuous progress can be achieved by selection for growth, the progeny of three second-generation Pacific oyster lines was selected for shell height and evaluated via a 400-day farming experiment. When harvested at the end of the experiment, the selected crosses of CS2, JS2, and KS2 lines grew by 9.2%, 10.2% and 9.6% larger than the control crosses, respectively. During grow-out stage, the genetic gain of three selected lines was (10.2 ± 1.4)%, (10.4 ± 0.3)%, and (8.4 ± 1.6)%, respectively; and the corresponding realized heritability was 0.457 ± 0.143, 0.312 ± 0.071 and 0.332 ± 0.009, respectively. These results indicated that the selection for fast growth achieved steady progress in the second generation of oyster. Our work provides supportive evidence for the continuity of the Pacific oyster selective breeding program.

Contextual Fear Extinction and Re-Extinction in Carioca High-and Low-Conditioned Freezing Rats

We recently reported two novel breeding lines of rats known as Carioca High- and Low-conditioned Freezing (CHF and CLF), based on defensive freezing responses to contextual cues previously associated with electric footshock. The present study used animals of the 8th generation of our selective breeding program to investigate both contextual fear extinction and re-extinction. The results consistently showed that CHF animals froze more than CLF animals. Long extinction training was able to extinguish phenotypic differences between lines, but the divergence was restored after just one fear reacquisition training session. These differences disappeared again during re-extinction training. The possible neural mechanisms involved in these two types of learning are discussed.

Apple leaf disease identification using genetic algorithm and correlation based feature selection method

Apple leaf disease is one of the main factors to constrain the apple production and quality.It takes a long time to detect the diseases by using the traditional diagnostic approach,thus farmers often miss the best time to prevent and treat the diseases.Apple leaf disease recognition based on leaf image is an essential research topic in the field of computer vision,where the key task is to find an effective way to represent the diseased leaf images.In this research,based on image processing techniques and pattern recognition methods,an apple leaf disease recognition method was proposed.A color transformation structure for the input RGB(Red,Green and Blue)image was designed firstly and then RGB model was converted to HSI(Hue,Saturation and Intensity),YUV and gray models.The background was removed based on a specific threshold value,and then the disease spot image was segmented with region growing algorithm(RGA).Thirty-eight classifying features of color,texture and shape were extracted from each spot image.To reduce the dimensionality of the feature space and improve the accuracy of the apple leaf disease identification,the most valuable features were selected by combining genetic algorithm(GA)and correlation based feature selection(CFS).Finally,the diseases were recognized by SVM classifier.In the proposed method,the selected feature subset was globally optimum.The experimental results of more than 90%correct identification rate on the apple diseased leaf image database which contains 90 disease images for there kinds of apple leaf diseases,powdery mildew,mosaic and rust,demonstrate that the proposed method is feasible and effective.

Simultaneous characterization of multiple properties of solid and liquid phases in crystallization processes using NIR

Near infrared spectroscopy （NIR） is now probably the most popular process analytical technology （PAT） for pharmaceutical and some other industries. However, unlike mid-IR, NIR is known to have difficulties in monitoring crystallization or precipitation processes because the existence of solids could cause distortion of the spectra. This phenomenon, seen as unfavorable previously, is however an indication that NIR spectra contain rich information about both solids and liquids, giving the possibility of using the same instrument for multiple property characterization. In this study, transflectance NIR calibration data was obtained using solutions and slurries of varied solution concentration, particle size, solid concentration and temperature. The data was used to build calibration models for prediction of the multiple properties of both phases. Predictive models were developed for this challenging application using an approach that combines genetic algorithm （GA） and support vector machine （SVM）. GA is used for wavelength selection and SVM for mode building. The new GA-SVM approach is shown to outperform other methods including GA-PLS （partial least squares） and traditional SVM. NIR is thus successfully applied to monitoring seeded and unseeded cooling crystallization processes of L-glutamic acid.

Population transcriptomics reveals a potentially positive role of expression diversity in adaptation

While it is widely accepted that genetic diversity determines the potential of adaptation,the role that gene expression variation plays in adaptation remains poorly known.Here we show that gene expression diversity could have played a positive role in the adaptation of Miscanthus lutarioriparius.RNA-seq was conducted for 80 individuals of the species,with half planted in the energy crop domestication site and the other half planted in the control site near native habitats.A leaf reference transcriptome consisting of 18,503 high-quality transcripts was obtained using a pipeline developed for de novo assembling with population RNA-seq data.The population structure and genetic diversity of M.lutarioriparius were estimated based on 30,609 genic single nucleotide polymorphisms.Population expression（Ep） and expression diversity（Ed）were defined to measure the average level and the magnitude of variation of a gene expression in the population,respectively.It was found that expression diversity increased while genetic Resediversity decreased after the species was transplanted from the native habitats to the harsh domestication site,especially for genes involved in abiotic stress resistance,histone methylation,and biomass synthesis under water limitation.The increased expression diversity could have enriched phenotypic variation directly subject to selections in the new environment.